3D Wavelet-Based Video Codec with Human Perceptual Model

This thesis explores the use of a human perceptual model in video compression, channel coding, error concealment and subjective image quality measurement. The perceptual distortion model just-noticeable-distortion (JND) is investigated. A video encoding/decoding scheme based on 3D wavelet decomposition and the human perceptual model is implemented. It provides a prior compression quality control which is distinct from the conventional video coding system. JND is applied in quantizer design to improve the subjective quality ofcompressed video. The 3D wavelet decomposition helps to remove spatial and temporal redundancy and provides scalability of video quality. In order to conceal the errors that may occur under bad wireless channel conditions, a slicing method and a joint source channel coding scenario that combines RCPC with CRC and uses the distortion information toallocate convolutional coding rates are proposed. A new subjective quality index based on JND is proposed and used to evaluate the overall performance at different signal to noise ratios (SNR) and at different compression ratios.Due to the wide use of arithmetic coding (AC) in data compression, we consider it as a readily available unit in the video codec system for broadcasting. A new scheme for conditional access (CA) sub-system is designed based on the cryptographic property of arithmetic coding. Itsperformance is analyzed along with its application in a multi-resolution video compression system. This scheme simplifies the conditional access sub-system and provides satisfactory system reliability

Codificação de vídeo: priorização do menor custo de codificação na otimização em taxa-distorção

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Elétrica, Florianópolis, 2009.O presente trabalho propõe duas novas estratégias para compressão de sinais de vídeo através de algoritmos otimizados em taxa-distorção (RD), focando aplicações típicas de vídeo digital para operação em baixas taxas de bits. As estratégias propostas são implementadas em um codificador de vídeo baseado no padrão H.264, o qual apresenta uma alta complexidade computacional devido principalmente ao grande número de modos de codificação disponível. São apresentadas duas propostas de redução da complexidade, mantendo o desempenho RD próximo àquele do codificador H.264 otimizado em RD usando busca exaustiva. A primeira proposta (denominada rate sorting and truncation - RST) realiza o ordenamento tanto dos vetores de movimento (VMs) quanto dos modos de codificação em ordem ascendente de taxa de bits. O processo de codificação é interrompido quando a taxa de bits dos novos VMs e modos de codificação exceder à menor taxa já obtida para um pré-estabelecido nível de qualidade de imagem. Assim, um grande número de VMs e diversos modos de codificação são descartados antes que sejam avaliados. A segunda proposta consiste em um algoritmo rápido, baseado no perfil de distribuição de vetores do codificador H.264, para estimação de movimento (denominado logarithmic diamond shape search - LDSS). O uso da estratégia RST associada ao algoritmo LDSS reduz até 98% a carga computacional com perda marginal de desempenho RD.This research work proposes two new video compression strategies, aiming at typical low bit rate video applications using rate-distortion (RD) optimized algorithms. The proposed strategies are implemented on an H.264 video encoder, which has high computational complexity due mainly to the large number of coding modes available. Two approaches are presented for reducing the encoder computational complexity, maintaining the RD performance close to the full search RD optimized H.264 encoder. The first approach (termed rate sorting and truncation - RST) is based on sorting the motion vectors (MVs) and coding modes in an ascending rate order. This sorting and encoding process, which is stopped when the rate value exceeds the previous best rate for a required image quality level, allows the elimination of MVs and coding modes before checking their distortion. Apart from obtaining a significant complexity reduction, the process still remains optimized in RD sense. The second approach is an algorithm (termed logarithmic diamond shape search - LDSS), which explores the MVs distribution profile for the RD optimized H.264 encoder. The use of the RST strategy associated with LDSS algorithm yields up to a 98% reduction in the computational burden, with insignificant RD performance loss

Procedimentos para metodo hibrido de compressão de imagens digitais utilizando transformadas Wavelet e codificação fractal

Orientador: Yuzo IanoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de ComputaçãoResumo: O principal obstáculo nas implementações da compressão fractal de images é o exaustivo tempo de codificação inerente. O objetivo desta pesquisa é introduzir uma nova aproximação para acelerar a codificação fractal de imagens através da aplicação da TWD e suas propriedades, sem que haja detrimento do PSNR ou da qualidade visual subjetiva. Logo, este trabalho apresenta um novo Codificador Híbrido Fractal-Wavelet, que aplica a compressão fractal acelerada à imagens estáticas decompostas pela transformada wavelet, explorando a correlação direcional das subimagens-wavelet. Este tipo de correlação foi constatada por Shapiro em outro contexto [2]. O esquema proposto promove melhor qualidade visual (compatível com as medidas de PSNR) e uma redução média de cerca de 80% no tempo de codificação-decodificação quando comparado aos resultados da codificação fractal pura para diversas imagens e taxas de bits. Adicionalmente os detalhes da imagem e as características de transmissão progressiva wavelet foram preservados. Nenhum artefato de blocagem, usualmente encontrados em codificadores fractais puros, resultou do processo de compressão híbrido. Os resultados deste trabalho demonstram o potencial da compressão híbrida fractal-wavelet como sendo uma ferramenta poderosa ainda a ser exploradaAbstract: The major drawback in the implementations of the fractal image compression is the exhaustive inherent encoding time. The objective of this research is to introduce a new approach to accelerate the fractal image coding through the application of the DWT and its properties without decrease in the PSNR as well as in the subjective visual quality. Thus, this work presents a New Fast Hybrid Fractal-Wavelet Image Coder that applies the accelerated fractal compression to wavelet transformed images by exploiting the directional correlation of the wavelet subimages. This kind of correlation was noticed by Shapiro in a different context [2]. The proposed scheme promotes better visual quality (compatible to the PSNR measures) and an average reduction of about 80% in encoding-decoding time when compared to the results of the pure accelerated fractal coding for several images and bitrates. Furthermore, the image details and the characteristics of wavelet progressive transmission are maintained; blocking effects, usually found in pure fractal coders, are not introduced. The results of this work demonstrate the potential of the fractal-wavelet hybrid compression as a powerful tool to be further explored.DoutoradoTelecomunicações e TelemáticaDoutor em Engenharia Elétric

SPIHT image coding : analysis, improvements and applications.

Image compression plays an important role in image storage and transmission. In the popular Internet applications and mobile communications, image coding is required to be not only efficient but also scalable. Recent wavelet techniques provide a way for efficient and scalable image coding. SPIHT (set partitioning in hierarchical trees) is such an algorithm based on wavelet transform. This thesis analyses and improves the SPIHT algorithm. The preliminary part of the thesis investigates two-dimensional multi-resolution decomposition for image coding using the wavelet transform, which is reviewed and analysed systematically. The wavelet transform is implemented using filter banks, and the z-domain proofs are given for the key implementation steps. A scheme of wavelet transform for arbitrarily sized images is proposed. The statistical properties of the wavelet coefficients (being the output of the wavelet transform) are explored for natural images. The energy in the transform domain is localised and highly concentrated on the low-resolution subband. The wavelet coefficients are DC-biased, and the gravity centre of most octave-segmented value sections (which are relevant to the binary bit-planes) is offset by approximately one eighth of the section range from the geometrical centre. The intra-subband correlation coefficients are the largest, followed by the inter-level correlation coefficients in the middle then the trivial inter-subband correlation coefficients on the same resolution level. The statistical properties reveal the success of the SPIHT algorithm, and lead to further improvements. The subsequent parts of the thesis examine the SPIHT algorithm. The concepts of successive approximation quantisation and ordered bit-plane coding are highlighted. The procedure of SPIHT image coding is demonstrated with a simple example. A solution for arbitrarily sized images is proposed. Seven measures are proposed to improve the SPIHT algorithm. Three DC-level shifting schemes are discussed, and the one subtracting the geometrical centre in the image domain is selected in the thesis. The virtual trees are introduced to hold more wavelet coefficients in each of the initial sets. A scheme is proposed to reduce the redundancy in the coding bit-stream by omitting the predictable symbols. The quantisation of wavelet coefficients is offset by one eighth from the geometrical centre. A pre-processing technique is proposed to speed up the judgement of the significance of trees, and a smoothing is imposed on the magnitude of the wavelet coefficients during the pre-processing for lossy image coding. The optimisation of arithmetic coding is also discussed. Experimental results show that these improvements to SPIHT get a significant performance gain. The running time is reduced by up to a half. The PSNR (peak signal to noise ratio) is improved a lot at very low bit rates, up to 12 dB in the extreme case. Moderate improvements are also made at high bit rates. The SPIHT algorithm is applied to loss less image coding. Various wavelet transforms are evaluated for lossless SPIHT image coding. Experimental results show that the interpolating transform (4, 4) and the S+P transform (2+2, 2) are the best for natural images among the transforms used, the interpolating transform (4, 2) is the best for CT images, and the bi-orthogonal transform (9, 7) is always the worst. Content-based lossless coding of a CT head image is presented in the thesis, using segmentation and SPIHT. Although the performance gain is limited in the experiments, it shows the potential advantage of content-based image coding

Significance-Linked Connected Component Analysis for Very Low Bit Rate Wavelet Video Coding

In recent years, a tremendous success in wavelet image coding has been achieved. It is mainly attributed to innovative strategies for data organization and representation of wavelet-transformed images. However, there have been only a few successful attempts in wavelet video coding. The most successful one is perhaps Sarnoff Corporation's zerotree entropy (ZTE) video coder. In the paper, a novel hybrid wavelet video coding algorithm termed video significance-linked connected component analysis (VSLCCA) is developed for very low bit rate applications. It has also been empirically evidenced that wavelet transform combined with those innovative data organization and representation strategies can be an invaluable asset in very low bit rate video coding as long as motion-compensated error frames are ensured to be blocking-effect-free or coherent. In the proposed VSLCCA codec, first, fine-tuned motion estimation based on H.263 Recommendation is developed to reduce temporal redundancy and exha..